Estimation of Integer Item Discriminations

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Description

Estimates integer item discrminations like in the one-parameter logistic model (OPLM; Verhelst & Glas, 1995). See Verhelst, Verstralen and Eggen (1991) for computational details.

Usage

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immer_opcat(a, hmean, min = 1, max = 10, maxiter = 200)

Arguments

a

Vector of estimated item discriminations

hmean

Prespecified harmonic mean

min

Minimum integer item discrmination

max

Maximum integer item discrimination

maxiter

Maximum number of iterations

Value

Vector containing integer item discriminations

Author(s)

Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

References

Verhelst, N. D. &, Glas, C. A. W. (1995). The one-parameter logistic model. In G. H. Fischer & I. W. Molenaar (Eds.). Rasch Models (pp. 215–238). New York: Springer.

Verhelst, N. D., Verstralen, H. H. F. M., & Eggen, T. H. J. M. (1991). Finding starting values for the item parameters and suitable discrimination indices in the one-parameter logistic model. CITO Measurement and Research Department Reports, 91-10.

See Also

See immer_cml for using immer_opcat to estimate the one-parameter logistic model.

Examples

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#############################################################################
# EXAMPLE 1: Estimating integer item discriminations for dichotomous data
#############################################################################

library(sirt)
data(data.read, package="sirt")
dat <- data.read
I <- ncol(dat)

#--- estimate 2PL model
mod <- sirt::rasch.mml2( dat , est.a = 1:I  , mmliter= 30)
summary(mod)
a <- mod$item$a		# extract (non-integer) item discriminations 

#--- estimate integer item discriminations under different conditions
a1 <- immer_opcat( a , hmean = 3 , min = 1 , max = 6 )
table(a1)
a2 <- immer_opcat( a , hmean = 2 , min = 1 , max = 3 )
a3 <- immer_opcat( a , hmean = 1.5 , min = 1 , max = 2 )
#--- compare results
cbind( a , a1 , a2 , a3)